Engineering Manager, ML Efficiency, AI Rapid Response Team
AI summary of the role
Engineering Manager role on Google's ML Efficiency team, acting as a player-coach to drive technical architecture and manage a team of AI/ML systems engineers.
What you’ll do
- Lead technical pathfinding and system design for the ML Efficiency Hub, driving complex 1–6 month Engineers and 2–4 week Strike Sprints.
- Design, prototype, and write production C++ and Python code for model distillation, speculative decoding, dynamic batching, and distributed serving systems.
- Take ill-defined executive mandates, de-risk technical feasibility within latency, FLOPs, and tokenomics thresholds, and deliver persuasive TVPs.
- Perform deep compute surgery on legacy P0 pipelines and establish Graceful Exit Packages for partner teams.
What you’ll bring
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing and launching software products, and 3 years with software design and architecture.
- 5 years of experience with ML design and ML infrastructure (model deployment, evaluation, data processing, debugging, fine tuning).
Technologies
C++ · Python · ML infrastructure · model distillation · speculative decoding · dynamic batching · distributed serving · XManager · BrainServer · SavedModel · Pathways · generative AI
About Google
Builds global consumer, ads, cloud, developer and AI platforms spanning Search, YouTube, Android, Workspace and Gemini.
Public
Source and classification
Deployment team leadership · Evidence for this classification:
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. As a Engineering Manager on the ML Efficiency team, you will serve as a pivotal player-coach, driving both technical architecture and formal engineering management for a high-performing team of AI/ML systems engineers. As an Engineering Manager, you will balance deep technical contributions with strategic pod leadership. You will lead Strike Sprints and embedded Forward Deployed Engineering (FDE) teams partnering with leadership across Google. You will take vague, high-stakes VP-level efficiency mandates, perform deep architectural surgery on enterprise pipelines, architect robust Thinnest Viable Proofs (TVPs), and cultivate an exceptional, high-velocity engineering culture.
More from the job description
About the job Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way. With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally. As a Engineering Manager on the ML Efficiency team, you will serve as a pivotal player-coach, driving both technical architecture and formal engineering management for a high-performing team of AI/ML systems engineers. As an Engineering Manager, you will balance deep technical contribu [... source excerpt omitted ...] y transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits Learn more about benefits at Google. Responsibilities Lead technical pathfinding and system design for the ML Efficiency Hub, driving complex 1–6 month En [... source excerpt omitted ...] gery on legacy P0 pipelines, evaluate complex architectural trade-offs, and establish concrete "Graceful Exit Packages" that set partner catching teams up for permanent autonomy. Qualifications Minimum qualifications: Bachelor’s degree or equivalent practical experience. 8 years of experience in software development. 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture. 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in anoth
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